Different computerized systems use data in different ways. The way in which data is used informs how the data is stored and maintained. To illustrate this widely recognized principle, the domains of data warehousing and data feeds will be briefly discussed.
A data warehouse is a database used for generating reports and data analysis. To facilitate reporting and data analysis functions, data is often transformed and organized in star schemas within a data warehouse. Populating the data within the data warehouse is done via ETL (Extract, Transform, Load) operations, which requires that the ETL system maintain, in addition to the current state of the data warehouse, information about the last incremental data extractions obtained from the source tables. ETL operations propagate incremental changes made at the source tables into the star schemas of the data warehouse. ETL operations may transform the data prior to loading the data into the data warehouse. Examples of such types of transformation include data cleansing, data standardization, surrogate key generation, surrogate key replacement, unit of measure conversion, and currency conversion. Business intelligence (BI) applications use data gathered from a data warehouse or a subset of the warehouse called a data mart.
A data feed is a stream of data which may allow the recipient to receive updated data from one or more data sources as the data changes at the data source. A data feed can supply data in the same format as the data source or in a different format (such as a star schema) which provides additional benefit to the recipient compared to how the data is expressed natively at the source.